Sports-related concussion is a growing health and socio-economical problem and yet, its biomechanical mechanisms are still poorly understood. Computational models of the human head are important tools to understand how mechanical energy from an external impact is transferred into regional brain mechanical responses sufficient to cause injury. However, current computational schemes require hours on a modern multi-CPU computer or even a supercomputer to simulate a single head impact, and are impractical to handle the amount of computations involved when studying a large athletic population on a large scale in the number of head impacts sustained. We propose to establish a pre-computed model response atlas to specifically address the computational challenges to allow efficient estimates of model responses without significant loss of accuracy. There are two specific aims. First, we will establish and evaluate the performance of a pre-computed model response atlas using a sophisticated finite element model of the human head developed in our group based on a large database of actual on-field head impact exposure. In the second aim, we will utilize the pre- computed atlas to investigate the significance of cumulative effects of repetitive head impacts and evaluate whether accumulated brain responses improve the sensitivity and specificity in concussion prediction and result in stronger and more significant correlations with neurocognitive alterations. These efforts will provide an important research tool to allow rapid exploration of brain biomechanics involved in sports-related concussion and offer an initial understanding on the significance of cumulative effects of repetitive head impacts. This proposal will leverage an existing large database of on-field head kinematics, neuroimaging findings, and clinical outcomes for helmeted athletes generated from previous NIH- and CDC-funded research efforts. The proposed research will accelerate exploration of the biomechanics that occur in individual brains subjected to actual on-field impacts which are expected to advance our understanding of which brain regions and are most susceptible to concussive injury.